DocumentCode
2394759
Title
Auto scene text detection based on edge and color features
Author
Huang, Xiaodong ; Liu, Kehua ; Zhu, Lishang
Author_Institution
Capital Normal Univ., Beijing, China
fYear
2012
fDate
19-20 May 2012
Firstpage
1882
Lastpage
1886
Abstract
In this paper we present a novel approach to detecting scene text based on the edge and color features. Firstly, because the character edge feature is not sensitive to the luminance changes, we extract the edge features to locate the candidate text region coarsely. Secondly, according to the text row character will keep similar color, we use the K-means clustering to extract color feature and locate the candidate text regions accurately. Finally, we use a trained SVM classifier to distinguish the text region from non-text region in these candidate regions. Experimental results show that our algorithm performs well for detecting scene text with various color, font-size and text alignment.
Keywords
edge detection; feature extraction; image colour analysis; support vector machines; text detection; SVM classifier training; autoscene text detection; character edge feature; color feature extraction; edge feature extraction; k-means clustering; luminance changes; nontext region; support vector machines; text alignment; text font-size; text region; text row character; Feature extraction; Image color analysis; Image edge detection; Lighting; Robustness; Support vector machines; Text recognition; K-means clustering; SVM; edge detection; scene text detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location
Yantai
Print_ISBN
978-1-4673-0198-5
Type
conf
DOI
10.1109/ICSAI.2012.6223415
Filename
6223415
Link To Document